Towards Music-Aware Virtual Assistants

We propose a system for modifying spoken notifications in a manner that is sensitive to the music a user is listening to. Spoken notifications provide convenient access to rich information without the need for a screen. Virtual assistants see prevalent use in hands-free settings such as driving or exercising, activities where users also regularly enjoy listening to music. In such settings, virtual assistants will temporarily mute a user’s music to improve intelligibility. However, users may perceive these interruptions as intrusive, negatively impacting their music-listening experience. To address this challenge, we propose the concept of music-aware virtual assistants, where speech notifications are modified to resemble a voice singing in harmony with the user’s music. We contribute a system that processes user music and notification text to produce a blended mix, replacing original song lyrics with the notification content. In a user study comparing musical assistants to standard virtual assistants, participants expressed that musical assistants fit better with music, reduced intrusiveness, and provided a more delightful listening experience overall.

Authors

Institutions

Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3654777.3676416
Citations
3
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
1.05
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Towards Music-Aware Virtual Assistants

Alexander Wang, Chris Donahue, David Lindlbauer
3 citations
Music and Audio Processing
1.05
article

Towards Music-Aware Virtual Assistants

Alexander Wang, Chris Donahue, David Lindlbauer
article en
3 citations

Abstract

We propose a system for modifying spoken notifications in a manner that is sensitive to the music a user is listening to. Spoken notifications provide convenient access to rich information without the need for a screen. Virtual assistants see prevalent use in hands-free settings such as driving or exercising, activities where users also regularly enjoy listening to music. In such settings, virtual assistants will temporarily mute a user’s music to improve intelligibility. However, users may perceive these interruptions as intrusive, negatively impacting their music-listening experience. To address this challenge, we propose the concept of music-aware virtual assistants, where speech notifications are modified to resemble a voice singing in harmony with the user’s music. We contribute a system that processes user music and notification text to produce a blended mix, replacing original song lyrics with the notification content. In a user study comparing musical assistants to standard virtual assistants, participants expressed that musical assistants fit better with music, reduced intrusiveness, and provided a more delightful listening experience overall.

Carnegie Mellon University (US)
Openalex Percentile: Top 23%
Music and Audio Processing
1.05
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.